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In this paper, we extend the idea of sparse representation into the high dimensional feature space induced by the kernel function, and propose a kernel based test sample sparse representation and classification algorithm (KTSRC) for the first time. The KTSRC is based on the assumption that the test sample can be linearly represented by a part of the training samples in the high dimensional feature...
Occlusion problem is one of remaining challenges in face recognition. This work expresses an occluded image as the summation of a non-occluded image and a sparse occlusion. By solving a l1 norm minimization problem, we isolate the sparse occlusion from the face image, and simultaneously reconstruct the image. The reconstructed image is same to the original one in most pixels. To classify an occluded...
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